#Number of distinct points to sample
#Every accepted point is included

#number of steps between independent samples
#if non-zero all info is dumped to file file_root.data
#if you change this probably have to change output routines in code too
indep_sample = 0

#number of samples to disgard at start
#May prefer to set to zero and remove later
burn_in = 0

#If zero set automatically
num_threads = 0

#MPI mode multi-chain options (recommended)
#MPI_Converge_Stop is a (variance of chain means)/(mean of variances) parameter that can be used to stop the chains
#Set to a negative number not to use this feature. Does not guarantee good accuracy of confidence limits.
MPI_Converge_Stop = 0.01
#if MPI_LearnPropose = T, the proposal density is continally updated from the covariance of samples so far (since burn in)
MPI_LearnPropose = T

#If have covmat, R to reach before updating proposal density (increase if covmat likely to be poor)
#Only used if not varying new parameters that are fixed in covmat
MPI_Max_R_ProposeUpdate = 2
#As above, but used if varying new parameters that were fixed in covmat
MPI_Max_R_ProposeUpdateNew = 30